Provenance — who produced it, who reused it
Linked to 1 papers in the literature. Roles are inferred factual signals (who deposited the data vs who reused it), with counts — never a judgement about any author.
1 further paper cites this accession but reuse could not be confirmed.
Deep data QC
83/100 · BStandardized, field-standard QC computed by touching the data — every metric states how it was obtained · evidence: measured
This is a small-RNA (miRNA-Seq) library from mouse, sequenced on an Illumina HiSeq 2000, and it earns a solid B (83/100) as a fundamentally sound but caveated dataset. The grade is held up by excellent base quality — 94.7% of bases at Q30 and a mean base quality of 36.1, with essentially zero adapter contamination and negligible N content — meaning the underlying reads are accurate and clean enough for confident miRNA mapping and quantification. The one metric dragging the score down is an 88.67% duplication rate (scored 0/100), which flags heavy read redundancy; for a miRNA library this is partly expected, since a small repertoire of short mature miRNAs is sequenced deeply, but it still caps true library complexity and means the ~2.6M reads represent fewer unique molecules than the raw count suggests — a real limit if you need sensitive detection of low-abundance miRNAs. Note also that the headline counts (total reads/bases, checksum) are reported rather than independently measured and the evidence_strength is 1, so while the per-base quality metrics are genuinely measured, the complexity and yield read should be treated as provisional pending a deeper measured pass.
The B grade is a transparent weighted average. Each metric below scored from 0–100% against the published bulk-RNA-seq thresholds, weighted by its importance; nothing is hidden or subjective.
measured = computed from the data · extrapolated/reported = derived or from the repository · dq-1.0
Scientific quality
Based on hands-on reproduction of the papers that use this dataset. A reproducible paper that stands on this data is positive evidence; a flagged one is a prompt to look closer — never a verdict on the dataset itself without the evidence.